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用于估计相互易位中不平衡后代风险的逻辑回归模型。

Logistic regression model to estimate the risk of unbalanced offspring in reciprocal translocations.

作者信息

Cans C, Cohen O, Lavergne C, Mermet M A, Demongeot J, Jalbert P

机构信息

Genetics Laboratory, Medical School, Joseph Fourier University Grenoble, La Tronche, France.

出版信息

Hum Genet. 1993 Dec;92(6):598-604. doi: 10.1007/BF00420946.

Abstract

The aim of this study was to estimate the risk of viable unbalanced offspring for a parental carrier of reciprocal translocation. On a large computerized database of reciprocal translocations we used logistic regression to model this risk. The status of the progeny is the outcome variable. Explanatory covariates are cytogenetic characteristics of the translocation, age and sex of the parental carrier, and potential viability of the gametes. The results obtained by the logistic model demonstrate the important role of certain variables such as the sex of the parental carrier and the R band length of the translocated segments. Within the group of lower risk (risk of viable unbalanced offspring less than 5%), 97% of the individuals are correctly classified with this model. For this group, the choice prenatal diagnosis can be best discussed by considering both the risk for viable unbalanced offspring and the risk of induced abortion following prenatal diagnosis.

摘要

本研究的目的是评估相互易位携带者生育存活的染色体不平衡后代的风险。在一个大型的相互易位计算机化数据库中,我们使用逻辑回归对这种风险进行建模。子代的状况是结果变量。解释性协变量包括易位的细胞遗传学特征、亲代携带者的年龄和性别以及配子的潜在活力。逻辑模型得到的结果表明某些变量的重要作用,如亲代携带者的性别和易位片段的R带长度。在低风险组(生育存活的染色体不平衡后代的风险小于5%)中,97%的个体通过该模型被正确分类。对于该组,最好通过综合考虑生育存活的染色体不平衡后代的风险以及产前诊断后人工流产的风险来讨论产前诊断的选择。

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